S16: SkyNet
Contents
Grading Criteria
- How well is Software & Hardware Design described?
- How well can this report be used to reproduce this project?
- Code Quality
- Overall Report Quality:
- Software Block Diagrams
- Hardware Block Diagrams
- Schematic Quality
- Quality of technical challenges and solutions adopted.
SkyNet
Meeting notes
This section is temporary and will only exist on the wiki during development.
| Date | Meeting Notes |
|---|---|
| 3/27 | Tracking:
C++ for OpenCV
Have target stand dead center and let the PC choose what to target
- Green for go
- red for lost
Graceful halt, error compensation in OpenCV layer
Motor System: API for % speed for x and y axis x_axis_speed(int speed_percent) y_axis_speed(int speed_percent) "Dumb motor system" should not know about error or destination, only knows how fast to go in a direction Enclosure: Visible framework 3D printing Autodesk Fusion 360 |
| TBA | +++++++ Meetings Notes ++++++++
PCB Design - Completed Design for PCB - Initial quote was 18 per board - Looking into the price and seeing other fab house prices - Aiming to get PCB in 2 weeks time Motor controller - Going to use TI controller as base - Fallback is Servo Motors - Motors used in robotic arms? slow and percise - Will be using EVM from TI to test out TI behavior - Looking into other controllers to get desired result L6234, SPWM signals (Sine-wave PWM) CAD Frame - Re-adjust Raspberry Pi Cubby on Horizontal Frame - Add more support to Horizontal Frame arms - Aiming to get test print by next meeting, test durability. OpenCV - Trained model for people detection already exists
- How to differentiate a person? Premade function gives back a list of everyone
- We CAN detect people, We need to find out how to narrrow down the targets
- Use rectangles to get coordinates combined with HSV
- Combine coordinates, analyze with HSV
- HAR face tracking
- possibly can single out a target
|
Abstract
SkyNet is a tracking tripod mount that will follow a given target using computer vision technologies. The system utilizes two brushless motors that are controlled by inputs given from a Raspberry Pi 3. The Raspberry Pi 3 utilizes the OpenCV open source library to calculate the deviation of a tracked object from the center of its view. It will then control the motors to correct the camera position such that the target will always be in the center of the video. The mount will be able to hold any standard 5-inch phone (should aim for universal mount) for video recording.
Objectives & Introduction
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Team Members & Responsibilities
- Steven Hwu
- OpenCV
- Jason Tran
- OpenCV
- Andrew Herbst
- Brushless Motor system
- Vince Ly
- Brushless Motor system
Schedule
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| Week# | Due Date | Task | Completed | Notes |
|---|---|---|---|---|
| 1 | 3/29 | - Create Parts list and place order (Motors, Cameras, etc.)
- Compile OpenCV C++ code and run examples on Raspberry Pi 3 |
Completed | - Ordered parts on 3/27
- OpenCV library is building on both development PCs (Steven/Jason) TODO: - Run OpenCV on Raspberry Pi 3 |
| 2 | 4/5 | - Create motorized unit
- Create the CAD model for 3D printing - Create the breakout board for the motor controller - Be able to track an object in frame (Highlight object) |
Completed | - Successfully tracked an object in HSV color space.
- Successfully tracked human w/ various other objects. - Human tracking not enough to track one person, trying combination of HSV tracking - Initial CAD model created w/ Autodesk Fusion 360 - Created PCB for TI chip, looking for fab houses |
| 3 | 4/12 | - Test various motors for behavior/control
- Extrapolate movement of object |
- Looking into Stepper vs Servo vs Brushless for optimal control/smoothness
- Looking into face tracking as option - Researching how to narrow down human tracking to 1 specific person. | |
| 4 | 4/19 | - Sync-up on how to command motors (scaling, etc.)
- Create API interface to control motors - Create communication tasks to control motors |
||
| 5 | 4/26 | - Integration of control system and motor unit | ||
| 6 | 5/3 | - Control Calibration
- Use case test |
||
| 7 | 5/10 | - Finish Report/Slide deck(?) |
Parts List & Cost
ECU:
RaspBerry Pi 3 Rev B
Brushless Motors:
x2 4008-70Kv Brushless Gimbal Motor ~$20
- http://www.hobbyking.com/hobbyking/store/__43041__4008_70Kv_Brushless_Gimbal_Motor_Ideal_for_mid_Style_Cameras_like_the_Nex6_.html
Controllers:
DRV11873
- http://www.ti.com/lit/ds/symlink/drv11873.pdf
Phone mount:
Vince's cheap ass mount ~Free
Whole Enclosure:
??? ~???
Design & Implementation
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Hardware Design
A custom frame was created to hold the motors and cameras in place. The initial design of the system was to use brushless motors to control the motion of the camera as an object was being tracked. This proved to be difficult because brushless motors have very high KV (rpm constant). This value is RPM/Volt, essentially a ratio to convert voltage to RPM. The motor initially being used was a motor rated at 70 KV.
Notes from 4/4
Other motors are being considered for this project which include servos and stepper motors. Servo motors have the problem of being too jittery/abrupt which is not ideal for recording video, this would defeat the purpose of the camera system. Stepper motors are also not ideal due to the fact that they are very heavy and require a large frame for the system to be structurally sound. Experiments will continue to verify which motor is ideal for the task.
Hardware Interface
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Software Design
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Implementation
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Testing & Technical Challenges
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My Issue #1
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Conclusion
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Project Video
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Project Source Code
References
Acknowledgement
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References Used
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Appendix
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